DataMasking

The Evolution of Data Security: Why Data Masking is a Game-Changer In today’s digital age, data security is top of mind for organizations worldwide. With the increasing frequency and sophistication of cyber-attacks, companies are under pressure to protect sensitive information. According to a recent study, 64% of organizations experienced a data breach in the past year, resulting in an average cost of $3.9 million (IBM Security, 2022). Data masking is a critical security measure that has gained significant traction in recent years. In this article, we’ll explore the latest industry trends and examine the benefits of data masking. ...

Introduction to Data Masking in Compensation and Benefits In today’s data-driven world, organizations are storing vast amounts of sensitive employee data, including compensation and benefits information. However, this sensitive data is often targeted by cyber attackers, putting the organization and its employees at risk. According to a study by IBM, the average cost of a data breach in 2020 was $3.86 million. To protect this sensitive data, organizations are turning to data masking. ...

Introduction In today’s data-driven world, organizations are collecting and storing vast amounts of sensitive information. However, this sensitive data is increasingly becoming a target for cyber attackers, identity thieves, and unauthorized access. As a result, data masking has become an essential technique for protecting sensitive data. In this blog post, we will conduct a comprehensive advantage analysis of data masking, exploring its benefits, use cases, and best practices. What is Data Masking? Data masking is a data security technique that involves hiding or obscuring sensitive data, making it unreadable or unusable to unauthorized users. This technique is used to protect sensitive data, such as credit card numbers, social security numbers, and personal identifiable information (PII). Data masking can be applied to various data types, including structured and unstructured data, and can be implemented in various environments, such as databases, file systems, and cloud storage. ...